The rapid advancement and integration of artificial intelligence (AI) into our everyday lives, work, and classrooms have added demands for PK-12 education to ensure that students are given opportunities to obtain AI competencies essential for responsible participation in the AI-driven future. AI literacy encompasses technical knowledge, ethical awareness, and critical evaluation of AI tools, as well as the ability to collaborate with AI systems in creative and productive ways. Research highlights the importance of age-appropriate approaches that address foundational AI knowledge, data literacy, ethics, problem-solving, and creativity, ensuring students can both use, analyze, critically evaluate, and design AI solutions for real-world challenges. This not only requires schools to prepare learners with AI competencies, but also colleges and universities to ensure that we prepare our preservice teachers to be AI-ready, who can integrate technological, pedagogical, and content knowledge in classroom practice. This paper highlights the importance of purposefully integrating AI competencies into teacher education programs and offers practical examples of how such integration can be achieved.

In recent years, the rapid advancement of artificial intelligence (AI) has fostered an urgent need to better prepare current and future educators to be able to integrate AI technologies in their teaching and to teach AI literacy to PreK-12 students. While many organizations have developed professional learning opportunities for inservice educators, a gap remains for resources specifically designed for those facilitating and enrolled in Educator Preparation Programs (EPPs). In response to this gap, the International Society for Technology in Education (ISTE) launched its first AI Explorations for EPPs Faculty Fellowship. As a result of the Faculty Fellows’ collaboration, this paper articulates a framework of seven critical strategies with the potential to address the urgent need EPPs have in preparing preservice teachers to effectively integrate AI-powered instructional tools and to teach this new area of content knowledge in PreK-12 classrooms. In addition, we provide a review of literature and an overview of the emerging needs for integrating AI education in EPPs. We demonstrate why support for preservice teachers’ critical examination and application of AI, including a focus on the issues of equity, ethics, and culturally responsive teaching, is essential to their later success in PreK-12 classrooms. Recommendations for further research and learning are also provided to promote community-wide initiatives for supporting the integration of AI in education through Educator Preparation Programs and beyond.

The Feature Detection tool is a web-based activity that allows students to detect features in images and build their own rule-based classification algorithms. In this paper, we introduce the tool and share how it is incorporated into two, 45-minute lessons. The objective of the first lesson is to introduce students to the concept of feature detection, or how a computer can break down visual input into lower-level features. The second lesson aims to show students how these lower-level features can be incorporated into rule-based models to classify higher-order objects. We discuss how this tool can be used as a "first step" to the more complex concept ideas of data representation and neural networks.

The Hands-On AI Projects for the Classroom series, a collection of five guides, includes interactive projects that can be used by teachers across grade levels and subject areas to teach K-12 students about artificial intelligence (AI).